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Record W2587261923 · doi:10.1002/agr.21496

Factors Affecting Changes in Managerial Decisions

2017· article· en· W2587261923 on OpenAlexaff
Joshua D. Woodard, Leslie J. Verteramo Chiu, Gabriel J. Power, Dmitry V. Vedenov, Steven L. Klose

Bibliographic record

VenueAgribusiness · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsUniversité Laval
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsEconLitProduction (economics)BusinessTime horizonMarketingAgricultureActuarial scienceEconomicsFinanceMicroeconomics

Abstract

fetched live from OpenAlex

ABSTRACT It is commonly held that revealed managerial decisions depend on the interaction of risk attitudes and preferences, as well as market and firm conditions. In agriculture, production plans can have a horizon of a few months to several years. However, it is not always the case that managers follow through on their plans once established. The purpose of this paper is to investigate factors that contribute to changes between managers’ planned decisions and eventual actions. A unique dataset consisting of farm financial data, consultant generated production plans, and a follow‐up producer survey was constructed with participants in the Texas FARM‐Assistance program. We evaluate the effects of managers’ behavioral attributes, farm financial indicators, and production characteristics on the decision to follow through on business plans. Our findings provide new insights into the decision‐making and planning processes of managers under risky market conditions, and the interactions of same with behavioral characteristics. [EconLit citations: Q12; Q13; Q14; D22; G02].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.262
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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